Impact of Deltoid Computer Tomography Image Data on the Accuracy of Machine Learning Predictions of Clinical Outcomes after Anatomic and Reverse Total Shoulder Arthroplasty.

Background: Despite the importance of the deltoid to shoulder biomechanics, very few studies have quantified the three-dimensional shape, size, or quality of the deltoid muscle, and no studies have correlated these measurements to clinical outcomes after anatomic (aTSA) and/or reverse (rTSA) total shoulder arthroplasty in any statistically/scientifically relevant manner. Methods: Preoperative computer tomography (CT) images from 1057 patients (585 female, 469 male; 799 primary rTSA and 258 primary aTSA) of a single platform shoulder arthroplasty prosthesis (Equinoxe; Exactech, Inc., Gainesville, FL) were analyzed in this study. A machine learning (ML) framework was used to segment the deltoid muscle for 1057 patients and quantify 15 different muscle characteristics, including volumetric (size, shape, etc.) and intensity-based Hounsfield (HU) measurements. These deltoid measurements were correlated to postoperative clinical outcomes and utilized as inputs to train/test ML algorithms used to predict postoperative outcomes at multiple postoperative timepoints (1 year, 2-3 years, and 3-5 years) for aTSA and rTSA. Results: Numerous deltoid muscle measurements were demonstrated to significantly vary with age, gender, prosthesis type, and CT image kernel; notably, normalized deltoid volume and deltoid fatty infiltration were demonstrated to be relevant to preoperative and postoperative clinical outcomes after aTSA and rTSA. Incorporating deltoid image data into the ML models improved clinical outcome prediction accuracy relative to ML algorithms without image data, particularly for the prediction of abduction and forward elevation after aTSA and rTSA. Analyzing ML feature importance facilitated rank-ordering of the deltoid image measurements relevant to aTSA and rTSA clinical outcomes. Specifically, we identified that deltoid shape flatness, normalized deltoid volume, deltoid voxel skewness, and deltoid shape sphericity were the most predictive image-based features used to predict clinical outcomes after aTSA and rTSA. Many of these deltoid measurements were found to be more predictive of aTSA and rTSA postoperative outcomes than patient demographic data, comorbidity data, and diagnosis data. Conclusions: While future work is required to further refine the ML models, which include additional shoulder muscles, like the rotator cuff, our results show promise that the developed ML framework can be used to evolve traditional CT-based preoperative planning software into an evidence-based ML clinical decision support tool.

The association between hemodynamics and wall characteristics in human intracranial aneurysms: a review.

Hemodynamics plays a key role in the natural history of intracranial aneurysms (IAs). However, studies exploring the association between aneurysmal hemodynamics and the biological and mechanical characteristics of the IA wall in humans are sparse. In this review, we survey the current body of literature, summarize the studies' methodologies and findings, and assess the degree of consensus among them. We used PubMed to perform a systematic review of studies that explored the association between hemodynamics and human IA wall features using different sources. We identified 28 publications characterizing aneurysmal flow and the IA wall: 4 using resected tissues, 17 using intraoperative images, and 7 using vessel wall magnetic resonance imaging (MRI). Based on correlation to IA tissue, higher flow conditions, such as high wall shear stress (WSS) with complex pattern and elevated pressure, were associated with degenerated walls and collagens with unphysiological orientation and faster synthesis. MRI studies strongly supported that low flow, characterized by low WSS and high blood residence time, was associated with thicker walls and post-contrast enhancement. While significant discrepancies were found among those utilized intraoperative images, they generally supported that thicker walls coexist at regions with prolonged residence time and that thinner regions are mainly exposed to higher pressure with complex WSS patterns. The current body of literature supports a theory of two general hemodynamic-biologic mechanisms for IA development. One, where low flow conditions are associated with thickening and atherosclerotic-like remodeling, and the other where high and impinging flow conditions are related to wall degeneration, thinning, and collagen remodeling.

Automated Cerebral Vessel Segmentation of Magnetic Resonance Imaging in Patients with Intracranial Atherosclerotic Diseases.

Time-of-flight (TOF) magnetic resonance angiography is a non-invasive imaging modality for the diagnosis of intracranial atherosclerotic diseases (ICAD). Evaluation of the degree of the stenosis and status of posterior and anterior communicating arteries to supply enough blood flow to the distal arteries is very critical, which requires accurate evaluation of arteries. Recently, deep-learning methods have been firmly established as a robust tool in medical image segmentation, which has been resulted in developing multiple customized algorithms. For instance, BRAVE-NET, a context-based successor of U-Net-has shown promising results in MRA cerebrovascular segmentation. Another widely used context-based 3D CNN-DeepMedic-has been shown to outperform U-Net in cerebrovascular segmentation of 3D digital subtraction angiography. In this study, we aim to train and compare the two state-of-the-art deep-learning networks, BRAVE-NET and DeepMedic, for automated and reliable brain vessel segmentation from TOF-MRA images in ICAD patients. Using specially labeled data-labeled on TOF MRA and corrected on high-resolution black-blood MRI, of 51 patients with ICAD due to severe stenosis, we trained and tested both models. On an independent test dataset of 11 cases, DeepMedic slightly outperformed BRAVE-NET in terms of DSC (0.905±0.012 vs 0.893±0.015, p: 0.539) and 95HD (0.754±0.223 vs 1.768±0.609, p: 0.134), and significantly outperformed BRAVE-NET in terms of Recall (0.940±0.023 vs 0.855±0.030, p: 0.036). Qualitative assessment confirmed the superiority of DeepMedic in capturing the small and distal arteries. While BRAVE-NET consistently reported higher precision, DeepMedic generally overpredicted and could better visualize the smaller and distal arteries. In future studies, ensemble models that can leverage best of both should be developed and tested on larger datasets.Clinical Relevance- This study helps elevate the state-of-the-art for brain vessel segmentation from non-invasive MRA, which could accelerate the translation of vessel status-based biomarkers into the clinical setting.

Aneurysm risk metrics and hemodynamics are associated with greater vessel wall enhancement in intracranial aneurysms.

Vessel wall enhancement (VWE) in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for intracranial aneurysm (IA) risk stratification. In this study, we investigated the relationship between VWE features, risk metrics, morphology and hemodynamics in 41 unruptured aneurysms. We reconstructed the IA geometries from MR angiography and mapped pituitary stalk-normalized MRI intensity on the aneurysm surface using an in-house tool. For each case, we calculated the maximum intensity (CRstalk) and IA risk (via size and the rupture resemblance score (RRS)). We performed correlation analysis to assess relationships between CRstalk and IA risk metrics (size and RRS), as well as each parameter encompassed in RRS, i.e. aneurysmal size ratio (SR), normalized wall shear stress (WSS) and oscillatory shear index. We found that CRstalk had a strong correlation (Pearson correlation coefficient, PCC = 0.630) with size and a moderate correlation (PCC = 0.472) with RRS, indicating an association between VWE and IA risk. Furthermore, CRstalk had a weak negative correlation with normalized WSS (PCC = -0.320) and a weak positive correlation with SR (PCC = 0.390). Local voxel-based analysis showed only a weak negative correlation between normalized WSS and contrast-enhanced MRI signal intensity (PCC = -0.240), suggesting that if low-normalized WSS induces enhancement-associated pathobiology, the effect is not localized.

An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms.

BACKGROUND: VWE in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for the evaluation of IA. The common practice to identify IAs with VWE is mainly based on a visual inspection of MR images, which is subject to errors and inconsistencies. Here, we develop and validate a tool for the visualization, quantification and objective identification of regions with VWE. METHODS: N = 41 3D T1-MRI and 3D TOF-MRA IA images from 38 patients were obtained and co-registered. A contrast-enhanced MRI was normalized by the enhancement intensity of the pituitary stalk and signal intensities were mapped onto the surface of IA models generated from segmented MRA. N = 30 IAs were used to identify the optimal signal intensity value to distinguish the enhancing and non-enhancing regions (marked by an experienced neuroradiologist). The remaining IAs (n = 11) were used to validate the threshold. We tested if the enhancement area ratio (EAR-ratio of the enhancing area to the IA surface-area) could identify high risk aneurysms as identified by the ISUIA clinical score. RESULTS: A normalized intensity of 0.276 was the optimal threshold to delineate enhancing regions, with a validation accuracy of 81.7%. In comparing the overlap between the identified enhancement regions against those marked by the neuroradiologist, our method had a dice coefficient of 71.1%. An EAR of 23% was able to discriminate high-risk cases with an AUC of 0.7. CONCLUSIONS: We developed and validated a pipeline for the visualization and objective identification of VWE regions that could potentially help evaluation of IAs become more reliable and consistent.

RNA Sequencing Data from Human Intracranial Aneurysm Tissue Reveals a Complex Inflammatory Environment Associated with Rupture.

BACKGROUND: Intracranial aneurysm (IA) rupture leads to deadly subarachnoid hemorrhages. However, the mechanisms leading to rupture remain poorly understood. Altered gene expression within IA tissue is linked to the pathobiology of aneurysm development and progression. Here, we analyzed expression patterns of control tissue samples and compared them to those of unruptured and ruptured IA tissue samples using data from the Gene Expression Omnibus (GEO). METHODS: FASTQ files for 21 ruptured IAs, 21 unruptured IAs, and 16 control tissue samples were accessed from the GEO database. DESeq2 was used for differential expression analysis in three comparisons: unruptured IA versus control, ruptured IA versus control, and ruptured versus unruptured IA. Genes that were differentially expressed in multiple comparisons were evaluated to find those progressively increasing/decreasing from control to unruptured to ruptured. Significance was tested by either analysis of variance/Gabriel or Brown-Forsythe/Games Howell (p < 0.05 was considered significant). We used additional RNA sequencing and proteomics datasets to evaluate if our differentially expressed genes (DEGs) were present in other studies. Bioinformatics analyses were performed with g:Profiler and Ingenuity Pathway Analysis. RESULTS: In total, we identified 1768 DEGs, of which 318 were found in multiple comparisons. Unruptured versus control reflected vascular remodeling processes, while ruptured versus control reflected inflammatory responses and cell activation/signaling. When comparing ruptured to unruptured IAs, we found massive activation of inflammation, inflammatory responses, and leukocyte responses. Of the 318 genes in multiple comparisons, 127 were found to be significant in the multi-cohort correlation analysis. Those that progressively increased (70 genes) were associated with immune system processes, while those that progressively decreased (38 genes) did not return any gene ontology terms. Many of our DEGs were also found in the other IA tissue sequencing studies. CONCLUSIONS: We found unruptured IAs relate more to remodeling processes, while ruptured IAs reflect more inflammatory and immune responses.

Identification of intima-to-media signals for flow-induced vascular remodeling using correlative gene expression analysis.

Changes in blood flow can induce arterial remodeling. Intimal cells sense flow and send signals to the media to initiate remodeling. However, the nature of such intima-media signaling is not fully understood. To identify potential signals, New Zealand white rabbits underwent bilateral carotid ligation to increase flow in the basilar artery or sham surgery (n = 2 ligated, n = 2 sham). Flow was measured by transcranial Doppler ultrasonography, vessel geometry was determined by 3D angiography, and hemodynamics were quantified by computational fluid dynamics. 24 h post-surgery, the basilar artery and terminus were embedded for sectioning. Intima and media were separately microdissected from the sections, and whole transcriptomes were obtained by RNA-seq. Correlation analysis of expression across all possible intima-media gene pairs revealed potential remodeling signals. Carotid ligation increased flow in the basilar artery and terminus and caused differential expression of 194 intimal genes and 529 medial genes. 29,777 intima-media gene pairs exhibited correlated expression. 18 intimal genes had > 200 medial correlates and coded for extracellular products. Gene ontology of the medial correlates showed enrichment of organonitrogen metabolism, leukocyte activation/immune response, and secretion/exocytosis processes. This demonstrates correlative expression analysis of intimal and medial genes can reveal novel signals that may regulate flow-induced arterial remodeling.

Aberrant Whole Blood Gene Expression in the Lumen of Human Intracranial Aneurysms.

The rupture of an intracranial aneurysm (IA) causes devastating hemorrhagic strokes. Yet, most IAs remain asymptomatic and undetected until they rupture. In the search for circulating biomarkers of unruptured IAs, we previously performed transcriptome profiling on whole blood and identified an IA-associated panel of 18 genes. In this study, we seek to determine if these genes are also differentially expressed within the IA lumen, which could provide a mechanistic link between the disease and the observed circulating gene expression patterns. To this end, we collected blood from the lumen of 37 IAs and their proximal parent vessels in 31 patients. The expression levels of 18 genes in the lumen and proximal vessel were then measured by quantitative polymerase chain reaction. This analysis revealed that the expression of 6/18 genes (CBWD6, MT2A, MZT2B, PIM3, SLC37A3, and TNFRSF4) was significantly higher in intraluminal blood, while the expression of 3/18 genes (ST6GALNAC1, TCN2, and UFSP1) was significantly lower. There was a significant, positive correlation between intraluminal and proximal expression of CXCL10, MT2A, and MZT2B, suggesting local increases of these genes is reflected in the periphery. Expression of ST6GALNAC1 and TIFAB was significantly positively correlated with IA size, while expression of CCDC85B was significantly positively correlated with IA enhancement on post-contrast MRI, a metric of IA instability and risk. In conclusion, intraluminal expression differences in half of the IA-associated genes observed in this study provide evidence for IA tissue-mediated transcriptional changes in whole blood. Additionally, some genes may be informative in assessing IA risk, as their intraluminal expression was correlated to IA size and aneurysmal wall enhancement.

Identification of Circulating Gene Expression Signatures of Intracranial Aneurysm in Peripheral Blood Mononuclear Cells.

Peripheral blood mononuclear cells (PBMCs) play an important role in the inflammation that accompanies intracranial aneurysm (IA) pathophysiology. We hypothesized that PBMCs have different transcriptional profiles in patients harboring IAs as compared to IA-free controls, which could be the basis for potential blood-based biomarkers for the disease. To test this, we isolated PBMC RNA from whole blood of 52 subjects (24 with IA, 28 without) and performed next-generation RNA sequencing to obtain their transcriptomes. In a randomly assigned discovery cohort of n = 39 patients, we performed differential expression analysis to define an IA-associated signature of 54 genes (q < 0.05 and an absolute fold-change ≥ 1.3). In the withheld validation dataset, these genes could delineate patients with IAs from controls, as the majority of them still had the same direction of expression difference. Bioinformatics analyses by gene ontology enrichment analysis and Ingenuity Pathway Analysis (IPA) demonstrated enrichment of structural regulation processes, intracellular signaling function, regulation of ion transport, and cell adhesion. IPA analysis showed that these processes were likely coordinated through NF-kB, cytokine signaling, growth factors, and TNF activity. Correlation analysis with aneurysm size and risk assessment metrics showed that 4/54 genes were associated with rupture risk. These findings highlight the potential to develop predictive biomarkers from PBMCs to identify patients harboring IAs.

Endogenous animal models of intracranial aneurysm development: a review.

The pathogenesis and natural history of intracranial aneurysm (IA) remains poorly understood. To this end, animal models with induced cerebral vessel lesions mimicking human aneurysms have provided the ability to greatly expand our understanding. In this review, we comprehensively searched the published literature to identify studies that endogenously induced IA formation in animals. Studies that constructed aneurysms (i.e., by surgically creating a sac) were excluded. From the eligible studies, we reported information including the animal species, method for aneurysm induction, aneurysm definitions, evaluation methods, aneurysm characteristics, formation rate, rupture rate, and time course. Between 1960 and 2019, 174 articles reported endogenous animal models of IA. The majority used flow modification, hypertension, and vessel wall weakening (i.e., elastase treatment) to induce IAs, primarily in rats and mice. Most studies utilized subjective or qualitative descriptions to define experimental aneurysms and histology to study them. In general, experimental IAs resembled the pathobiology of the human disease in terms of internal elastic lamina loss, medial layer degradation, and inflammatory cell infiltration. After the early 2000s, many endogenous animal models of IA began to incorporate state-of-the-art technology, such as gene expression profiling and 9.4-T magnetic resonance imaging (MRI) in vivo imaging, to quantitatively analyze the biological mechanisms of IA. Future studies aimed at longitudinally assessing IA pathobiology in models that incorporate aneurysm growth will likely have the largest impact on our understanding of the disease. We believe this will be aided by high-resolution, small animal, survival imaging, in situ live-cell imaging, and next-generation omics technology.

Landmark-Based Shape Analysis on Middle Cerebral Intracranial Aneurysms: A Geometric Morphometrics Approach to Infer Natural History.

BACKGROUND: Due to the scarcity of longitudinal data, the morphologic development of intracranial aneurysms (IAs) during their natural history remains poorly understood. However, longitudinal information can often be inferred from cross-sectional datasets as demonstrated by anatomists' use of geometric morphometrics to build evolutionary trees, reconstructing species inter-relationships based on morphologic landmarks. OBJECTIVE: We adopted these tools to analyze cross-sectional image data and infer relationships between IA morphologies. METHODS: On 3D reconstructions of 52 middle cerebral arteries (MCA) IAs (9 ruptured) and 10 IAfree MCAs (baseline geometries), 7 semi-automated landmarks were placed at the proximal parent artery and maximum height. From these, 64 additional landmarks were computationally generated to create a 71-landmark point cloud of 213 xyz coordinates. This data was normalized by Procrustes transformation and used in the principal component analysis, hierarchical clustering, and phylogenetic analyses. RESULTS: Principal component analysis showed separation of IA-free MCA geometries and grouping of ruptured IAs from unruptured IAs. Hierarchical clustering delineated a cluster of only unruptured IAs that were significantly smaller and more spherical than clusters that had ruptured IAs. Phylogenetic classification placed ruptured IAs more distally in the tree than unruptured IAs, indicating greater shape derivation. Groups of unruptured IAs were observed, but ruptured IAs were invariably found in mixed lineages with unruptured IAs, suggesting that some pathways of shape change may be benign while others are more associated with rupture. CONCLUSION: Geometric morphometric analyses of larger datasets may indicate particular pathways of shape change leading toward aneurysm rupture versus stabilization.

A data-driven model to identify high-risk aneurysms and guide management decisions: the Rupture Resemblance Score.

OBJECTIVE: Previous studies have found that ruptured intracranial aneurysms (RIAs) have distinct morphological and hemodynamic characteristics, including higher size ratio and oscillatory shear index and lower wall shear stress. Unruptured intracranial aneurysms (UIAs) that possess similar characteristics to RIAs may be at a higher risk of rupture than those UIAs that do not. The authors previously developed the Rupture Resemblance Score (RRS), a data-driven computer model that can objectively gauge the similarity of UIAs to RIAs in terms of morphology and hemodynamics. The authors aimed to explore the clinical utility of RRS in guiding the management of UIAs, especially for challenging cases such as small UIAs. METHODS: Between September 2018 and June 2019, the authors retrospectively collected consecutive challenging cases of incidentally identified UIAs that were discussed during their weekly multidisciplinary neurovascular conference. From patient 3D digital subtraction angiography, they reconstructed the aneurysm geometry and performed computer-assisted 3D morphology analysis and computational fluid dynamics simulation. They calculated RRS for every UIA case and compared it against the treatment decision made at the neurovascular conference as well as the recommendation based on the unruptured intracranial aneurysm treatment score (UIATS). RESULTS: Forty-seven patients with 79 UIAs, 90% of which were < 7 mm in size, were included in this study. The mean RRS (range 0.0-1.0) was 0.24 ± 0.31. At the conferences, treatment was endorsed for 45 of the UIAs (57%). These cases had significantly higher RRSs than the 34 cases suggested for observation (0.33 ± 0.34 vs 0.11 ± 0.19, p < 0.001). The UIATS-based recommendations were "observation" for 24 UIAs (30%), "treatment" for 21 UIAs (27%), and "not definitive" for 34 UIAs (43%). These "not definitive" cases were stratified by RRS based on similarity to RIAs. CONCLUSIONS: Although not a rupture predictor, RRS is a data-driven model that gauges the similarity of UIAs to RIAs in terms of morphology and hemodynamics. In cases in which the UIATS-based recommendation is not definitive, RRS provides additional stratification to assist the identification of high-risk UIAs. The current study highlights the clinical utility of RRS in a real-world setting as an adjunctive tool for the management of UIAs.

Inter-patient variations in flow boundary conditions at middle cerebral artery from 7T PC-MRI and influence on Computational Fluid Dynamics of intracranial aneurysms.

BACKGROUND: Computational fluid dynamics(CFD) of intracranial aneurysms requires flow boundary conditions(BCs) as inputs. Patient-specific BCs are usually unavailable and substituted by literature-derived generic BCs. Therefore, we investigated inter-patient BC variations and their influence on middle cerebral artery aneurysmal hemodynamics. METHOD: We retrospectively collected CT angiography and 7-T Phase-Contrast(PC)-MRI data from eight middle-cerebral-artery bifurcation aneurysms to reconstruct the geometry and measure the arterial flowrates, respectively. The coefficient of variation(CoV) was calculated for the inlet flowrate and the pulsatility index(PI). The outflow split estimated by Murray's law was compared with PC-MRI measurements. For each aneurysm, we performed seven simulations: "baseline" using PC-MRI-derived BCs and the other six with changing BCs to explore the influence of BC variations on hemodynamics. RESULTS: From PC-MRI, the inlet flowrate was 1.94 ± 0.71 cm3/s(CoV = 36%) and PI was 0.37 ± 0.13(CoV = 34%). The outflow split estimated by Murray's law deviated by 15.3% compared to PC-MRI. Comparing to "baseline" models, ±36% variations in inlet flowrate caused -61% to +89% changes in time-averaged wall shear stress(WSS), -37% to +32% in normalized WSS(NWSS; by parent-artery), and -42% to +126% in oscillatory shear index(OSI). The ±34% variations in PI caused, -46% to +67% in OSI. Applying ±15% variations in outflow split led to inflow jet deflection and -41% to +52% changes in WSS, -41% to +47% in NWSS, and -44% to +144% in OSI. CONCLUSION: Inflow rate and outflow split have a drastic impact on hemodynamics of intracranial aneurysms. Inlet waveform has a negligible impact on WSS and NWSS but major impact on OSI. CFD-based models need to consider such sensitivity.

Collagen Turnover in Relation to Risk Factors and Hemodynamics in Human Intracranial Aneurysms.

Background and Purpose- Determinants for molecular and structural instability, that is, impending growth or rupture, of intracranial aneurysms (IAs) remain uncertain. To elucidate this, we endeavored to estimate the actual turnover rates of the main molecular constituent in human IA (collagen) on the basis of radiocarbon (14C) birth dating in relation to IA hemodynamics. Methods- Collagen turnover rates in excised human IA samples were calculated using mathematical modeling of 14C birth dating data of collagen in relation to risk factors and histological markers for collagen maturity/turnover in selected IA. Hemodynamics were simulated using image-based computational fluid dynamics. Correlation, logistic regression, and receiver operating characteristic analyses were performed. Results- Collagen turnover rates were estimated in 46 IA (43 patients); computational fluid dynamics could be performed in 20 IA (20 patients). The mean collagen turnover rate (γ) constituted 126% (±1% error) per year. For patients with arterial hypertension, γ was greater than 2600% annually, whereas γ was distinctly lower with 32% (±1% error) per year for patients without risk factors, such as smoking and hypertension. There was a distinct association between histological presence of rather immature collagen in human IA and the presence of modifiable risk factors. Spatial-temporal averaged wall shear stress predicted rapid collagen turnover (odds ratio, 1.6 [95% CI, 1.0-2.7]). Receiver operating characteristic analysis demonstrated a good test accuracy (area under the curve, 0.798 [95% CI, 0.598-0.998]) for average wall shear stress with a threshold ≥4.9 Pa for rapid collagen turnover. Conclusions- Our data indicate that turnover rates and stability of collagen in human IA are strongly associated with the presence of modifiable risk factors and aneurysmal hemodynamics. These findings underline the importance of strict risk factor modification in patients with unruptured IA. Future should include more detailed risk factor data to establish a more causal understanding of hemodynamics and the rupture risk of individual IA.

Size of ruptured intracranial aneurysms: a systematic review and meta-analysis.

BACKGROUND: There is wide variation in the reported size of ruptured intracranial aneurysms and methods of size estimation. There is widespread belief that small aneurysms < 7 mm do not rupture. Therefore, we performed a systematic review and meta-analysis of the literature to determine the size of ruptured aneurysms according to aneurysm locations and methods of size estimation. METHODS: We searched PubMed, Cochrane, CINAHL, and EMBASE databases using a combination of Medical Subject Headings (MeSH) terms. We included articles that reported mean aneurysm size in consecutive series of ruptured intracranial. We excluded studies limited to a specific aneurysm location or type. The random-effects model was used to calculate overall mean size and location-specific mean size. We performed meta-regression to explain observed heterogeneity and variation in reported size. RESULTS: The systematic review included 36 studies and 12,609 ruptured intracranial aneurysms. Overall mean aneurysm size was 7.0 mm (95% confidence interval [CI 6.2-7.4]). Pooled mean size varied with location. Overall mean size of 2145 ruptured anterior circulation aneurysms was 6.0 mm (95% CI 5.6-6.4, residual I2 = 86%). Overall mean size of 743 ruptured posterior circulation aneurysms was 6.2 mm (95% CI 5.3-7.0, residual I2 = 93%). Meta-regression identified aneurysm location and definition of size (i.e., maximum dimension vs. aneurysm height) as significant determinants of aneurysm size reported in the studies. CONCLUSIONS: The mean size of ruptured aneurysms in most studies was approximately 7 mm. The general wisdom that aneurysms of this size do not rupture is incorrect. Location and size definition were significant determinants of aneurysm size.

Evaluation of Two Fast Virtual Stenting Algorithms for Intracranial Aneurysm Flow Diversion.

BACKGROUND: Endovascular treatment of intracranial aneurysms (IAs) by flow diverter (FD) stents depends on flow modification. Patient-specific modeling of FD deployment and computational fluid dynamics (CFD) could enable a priori endovascular strategy optimization. We developed a fast, simplistic, expansion-free balls-weeping algorithm to model FDs in patientspecific aneurysm geometry. However, since such strong simplification could result in less accurate simulations, we also developed a fast virtual stenting workflow (VSW) that explicitly models stent expansion using pseudo-physical forces. METHODS: To test which of these two fast algorithms more accurately simulates real FDs, we applied them to virtually treat three representative patient-specific IAs. We deployed Pipeline Embolization Device into 3 patient-specific silicone aneurysm phantoms and simulated the treatments using both balls-weeping and VSW algorithms in computational aneurysm models. We then compared the virtually deployed FD stents against experimental results in terms of geometry and post-treatment flow fields. For stent geometry, we evaluated gross configurations and porosity. For post-treatment aneurysmal flow, we compared CFD results against experimental measurements by particle image velocimetry. RESULTS: We found that VSW created more realistic FD deployments than balls-weeping in terms of stent geometry, porosity and pore density. In particular, balls-weeping produced unrealistic FD bulging at the aneurysm neck, and this artifact drastically increased with neck size. Both FD deployment methods resulted in similar flow patterns, but the VSW had less error in flow velocity and inflow rate. CONCLUSION: In conclusion, modeling stent expansion is critical for preventing unrealistic bulging effects and thus should be considered in virtual FD deployment algorithms. Also endowed with its high computational efficiency and superior accuracy, the VSW algorithm is a better candidate for implementation into a bedside clinical tool for FD deployment simulation.

Morphologic Parameters and Location Associated with Rupture Status of Intracranial Aneurysms in Elderly Patients.

BACKGROUND: Treatment of unruptured intracranial aneurysms (IAs) in elderly patients is associated with a high risk of morbidity and mortality, necessitating a thorough understanding of the potential rupture risk. The aim of this study was to identify morphologic parameters and anatomic locations that could discriminate ruptured IAs in patients ≥70 years old. METHODS: Retrospective analysis was performed of three-dimensional angiograms and medical records of 344 patients with 411 saccular IAs. Patients ≥70 years old were defined as elderly. IAs were subdivided into ruptured and unruptured. Morphologic parameters and anatomic locations were compared in elderly and younger (<70 years old) patients with ruptured and unruptured IAs. RESULTS: The study included 266 patients <70 years old and 78 patients ≥70 years old with 411 aneurysms (102 ruptured and 309 unruptured). In the elderly group, 22 of 95 aneurysms were ruptured (23.15%) compared with 80 of 316 (25.3%) in the younger group. Size ratio and aspect ratio were higher in ruptured IAs, but only in the younger group. Undulation index, indicating IA shape irregularity, was significantly different between ruptured and unruptured IAs in younger and elderly groups. The only variables associated with rupture in the elderly group were undulation index (0.11 ± 0.07 vs. 0.07 ± 0.06, P = 0.02) and location (P = 0.001). CONCLUSIONS: Aneurysm size, size ratio, and aspect ratio may not be reliable discriminants of rupture in elderly patients. Unruptured IAs in elderly patients should be evaluated on the basis of shape irregularity and anatomic location.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-phase II: rupture risk assessment.

PURPOSE: Assessing the rupture probability of intracranial aneurysms (IAs) remains challenging. Therefore, hemodynamic simulations are increasingly applied toward supporting physicians during treatment planning. However, due to several assumptions, the clinical acceptance of these methods remains limited. METHODS: To provide an overview of state-of-the-art blood flow simulation capabilities, the Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was conducted. Seventeen research groups from all over the world performed segmentations and hemodynamic simulations to identify the ruptured aneurysm in a patient harboring five IAs. Although simulation setups revealed good similarity, clear differences exist with respect to the analysis of aneurysm shape and blood flow results. Most groups (12/71%) included morphological and hemodynamic parameters in their analysis, with aspect ratio and wall shear stress as the most popular candidates, respectively. RESULTS: The majority of groups (7/41%) selected the largest aneurysm as being the ruptured one. Four (24%) of the participating groups were able to correctly select the ruptured aneurysm, while three groups (18%) ranked the ruptured aneurysm as the second most probable. Successful selections were based on the integration of clinically relevant information such as the aneurysm site, as well as advanced rupture probability models considering multiple parameters. Additionally, flow characteristics such as the quantification of inflow jets and the identification of multiple vortices led to correct predictions. CONCLUSIONS: MATCH compares state-of-the-art image-based blood flow simulation approaches to assess the rupture risk of IAs. Furthermore, this challenge highlights the importance of multivariate analyses by combining clinically relevant metadata with advanced morphological and hemodynamic quantification.

9.4T Magnetic Resonance Imaging of the Mouse Circle of Willis Enables Serial Characterization of Flow-Induced Vascular Remodeling by Computational Fluid Dynamics.

BACKGROUND: The neurovasculature dynamically responds to changes in cerebral blood flow by vascular remodeling processes. Serial imaging studies in mouse models could help characterize pathologic and physiologic flow-induced remodeling of the Circle of Willis (CoW). METHOD: We induced flow-driven pathologic cerebral vascular remodeling in the CoW of mice (n=3) by ligation of the left Common Carotid Artery (CCA), and the right external carotid and pterygopalatine arteries, increasing blood flow through the basilar and the right internal carotid arteries. One additional mouse was used as a wild-type control. Magnetic Resonance Imaging (MRI) at 9.4 Tesla (T) was used to serially image the mouse CoW over three months, and to obtain threedimensional images for use in Computational Fluid Dynamic (CFD) simulations. Terminal vascular corrosion casting and scanning electron microscope imaging were used to identify regions of macroscopic and microscopic arterial damage. RESULTS: We demonstrated the feasibility of detecting and serially measuring pathologic cerebral vascular changes in the mouse CoW, specifically in the anterior vasculature. These changes were characterized by bulging and increased vessel tortuosity on the anterior cerebral artery and aneurysm- like remodeling at the right olfactory artery origin. The resolution of the 9.4T system further allowed us to perform CFD simulations in the anterior CoW, which showed a correlation between elevated wall shear stress and pathological vascular changes. CONCLUSION: In the future, serial high-resolution MRI could be useful for characterizing the flow environments corresponding to other pathologic remodeling processes in the mouse CoW, such as aneurysm formation, subarachnoid hemorrhage, and ischemia.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): Phase I: Segmentation.

PURPOSE: Advanced morphology analysis and image-based hemodynamic simulations are increasingly used to assess the rupture risk of intracranial aneurysms (IAs). However, the accuracy of those results strongly depends on the quality of the vessel wall segmentation. METHODS: To evaluate state-of-the-art segmentation approaches, the Multiple Aneurysms AnaTomy CHallenge (MATCH) was announced. Participants carried out segmentation in three anonymized 3D DSA datasets (left and right anterior, posterior circulation) of a patient harboring five IAs. Qualitative and quantitative inter-group comparisons were carried out with respect to aneurysm volumes and ostia. Further, over- and undersegmentation were evaluated based on highly resolved 2D images. Finally, clinically relevant morphological parameters were calculated. RESULTS: Based on the contributions of 26 participating groups, the findings reveal that no consensus regarding segmentation software or underlying algorithms exists. Qualitative similarity of the aneurysm representations was obtained. However, inter-group differences occurred regarding the luminal surface quality, number of vessel branches considered, aneurysm volumes (up to 20%) and ostium surface areas (up to 30%). Further, a systematic oversegmentation of the 3D surfaces was observed with a difference of approximately 10% to the highly resolved 2D reference image. Particularly, the neck of the ruptured aneurysm was overrepresented by all groups except for one. Finally, morphology parameters (e.g., undulation and non-sphericity) varied up to 25%. CONCLUSIONS: MATCH provides an overview of segmentation methodologies for IAs and highlights the variability of surface reconstruction. Further, the study emphasizes the need for careful processing of initial segmentation results for a realistic assessment of clinically relevant morphological parameters.